In the field of medical image processing, various processing tasks are typically performed on medical images like ultrasound images, MRT images, computer tomography images or the like. One specific processing task, which is a fundamental task in many image processing applications, is the segmentation of a region of interest e.g. a specific organ. The segmentation is necessary for identifying organs or for special diagnosis e.g. based on volume quantification in order to improve the determination of treatment parameters.
For many organs, the image segmentation can successfully be performed with deformable models, which are based on a mesh structure with a topology which remains unchanged during adaptation to the image being segmented. Model-based segmentation has been considered very efficient for a wide variety of simple to complex organs like bones, liver, heart with nested structures. A corresponding method for facilitating of images using deformable meshes is e.g. known from WO 2007/072363.
WO 2011/070464 A2 discloses a system and a method for automatic segmentation, performed by selecting a deformable model of an anatomical structure of interest imaged in a volumetric image, wherein the deformable model is formed of a plurality of polygons including vertices and edges, wherein a feature point of the anatomical structure of interest corresponding to each of the plurality of polygons is detected and the deformable model is adapted by moving each of the vertices toward the corresponding feature point until the deformable model morphs to a boundary of the anatomical structure of interest.
WO 2006/029037 A2 discloses a system and a method for defining and tracking a deformable shape of a candidate anatomical structure wall in a three-dimensional image, wherein the shape of the candidate anatomical structure is represented by a plurality of labeled 3D landmark points and at least one 3D landmark point of the deformable shape in an image frame is defined.
Although model-based segmentations generally provide a reliable and accurate identification and segmentation of the organs, some anatomical structures like the apex of the left ventricle of the heart, or the tip of the liver or the horn of the ventricles of the brain are often difficult to detect in the medical images so that the segmentation of these features is challenging.